接口性能优化十倍，来了解一下Arthas的强大！
1背景
Helios 系统要处理的数据量比较大，尤其是查询所有服务一天的评分数据时要返回每日 1440 分钟的所有应用的评分，总计有几十万个数据点，接口有时延迟会达到数秒。
本文记录如何利用 Arthas ，将接口从几百几千 ms，优化到几十 ms。
从链路上看，线上获取一整天的数据时大概 300 多 ms，而查询数据库只有 11ms，说明大部分时间都是程序组装数据时消耗的，于是动起了优化代码的念头。
基于 Spring Boot + MyBatis Plus + Vue & Element 实现的后台管理系统 + 用户小程序，支持 RBAC 动态权限、多租户、数据权限、工作流、三方登录、支付、短信、商城等功能
- 项目地址：https://github.com/YunaiV/ruoyi-vue-pro
- 视频教程：https://doc.iocoder.cn/video/
2优化过程
代码业务可以不用去理解，最主要的是看利用trace优化的过程
基于 Spring Cloud Alibaba + Gateway + Nacos + RocketMQ + Vue & Element 实现的后台管理系统 + 用户小程序，支持 RBAC 动态权限、多租户、数据权限、工作流、三方登录、支付、短信、商城等功能
3初始未优化版本
代码
privateHeliosGetScoreResponsequeryScores(HeliosGetScoreRequestrequest){
HeliosGetScoreResponseresponse=newHeliosGetScoreResponse();
ListheliosScores=heliosService.queryScoresTimeBetween(request.getStartTime(),request.getEndTime(),request.getFilterByAppId());
if(CollectionUtils.isEmpty(heliosScores)){
returnresponse;
}
SetdateSet=newHashSet<>();
Map>groupByAppIdHeliosScores=heliosScores.stream().collect(Collectors.groupingBy(HeliosScore::getAppId));
for(Listvalue:groupByAppIdHeliosScores.values()){
value.sort(Comparator.comparing(HeliosScore::getTimeFrom));
HeliosGetScoreResponse.Scorescore=newHeliosGetScoreResponse.Score();
score.setNamespace(value.get(0).getNamespace());
score.setAppId(value.get(0).getAppId());
for(HeliosScoreheliosScore:value){
ListsplitHeliosScores=heliosScore.split();
for(HeliosScoresplitHeliosScore:splitHeliosScores){
if(splitHeliosScore.getTimeFrom().compareTo(request.getStartTime())< 0){
continue;
}
if(splitHeliosScore.getTimeFrom().compareTo(request.getEndTime())>0){
break;
}
dateSet.add(DateUtils.yyyyMMddHHmm.formatDate(splitHeliosScore.getTimeFrom()));
if(splitHeliosScore.getScores()==null){
splitHeliosScore.setScores("100");
log.error("查询时发现数据缺失:{}",heliosScore);
}
score.add(Math.max(0,Integer.parseInt(splitHeliosScore.getScores())),null);
}
}
response.getValues().add(score);
}
response.setDates(newArrayList<>(dateSet).stream().sorted().collect(Collectors.toList()));
returnresponse;
}
Arthas Trace
---ts=2021-08-1716:28:00;thread_name=http-nio-8080-exec-10;id=81;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@20864cd1
`---[4046.398447ms]xxxService.controller.HeliosController:queryScores()
+---[0.022259ms]xxxService.model.helios.HeliosGetScoreResponse:()#147
+---[0.007132ms]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#149
+---[0.006985ms]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#149
+---[0.008704ms]xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId()#149
+---[19.284658ms]xxxService.service.HeliosService:queryScoresTimeBetween()#149
+---[0.017468ms]org.apache.commons.collections.CollectionUtils:isEmpty()#150
+---[0.008054ms]java.util.HashSet:()#154
+---[0.027591ms]java.util.List:stream()#156
+---[0.044229ms]java.util.stream.Collectors:groupingBy()#156
+---[0.155582ms]java.util.stream.Stream:collect()#156
+---[0.018318ms]java.util.Map:values()#157
+---[0.019199ms]java.util.Collection:iterator()#157
+---[min=3.51E-4ms,max=0.014266ms,total=0.125003ms,count=123]java.util.Iterator:hasNext()#157
+---[min=5.11E-4ms,max=0.010188ms,total=0.145693ms,count=122]java.util.Iterator:next()#157
+---[min=4.89E-4ms,max=0.045356ms,total=0.321978ms,count=122]java.util.Comparator:comparing()#158
+---[min=0.003637ms,max=0.033049ms,total=0.928795ms,count=122]java.util.List:sort()#158
+---[min=5.94E-4ms,max=0.010442ms,total=0.1485ms,count=122]xxxService.model.helios.HeliosGetScoreResponse$Score:()#159
+---[min=4.5E-4ms,max=0.010857ms,total=0.12773ms,count=122]java.util.List:get()#160
+---[min=5.01E-4ms,max=0.007849ms,total=0.123696ms,count=122]xxxService.helios.entity.HeliosScore:getNamespace()#160
+---[min=6.5E-4ms,max=0.007324ms,total=0.135906ms,count=122]xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace()#160
+---[min=3.72E-4ms,max=0.010288ms,total=0.086703ms,count=122]java.util.List:get()#161
+---[min=5.1E-4ms,max=0.00627ms,total=0.103871ms,count=122]xxxService.helios.entity.HeliosScore:getAppId()#161
+---[min=5.97E-4ms,max=0.006531ms,total=0.126184ms,count=122]xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId()#161
+---[min=4.45E-4ms,max=0.020198ms,total=0.138299ms,count=122]java.util.List:iterator()#162
+---[min=3.42E-4ms,max=0.014615ms,total=0.256056ms,count=366]java.util.Iterator:hasNext()#162
+---[min=3.59E-4ms,max=0.014974ms,total=0.174396ms,count=244]java.util.Iterator:next()#162
+---[min=0.071035ms,max=0.148132ms,total=19.444179ms,count=244]xxxService.helios.entity.HeliosScore:split()#163
+---[min=4.06E-4ms,max=0.022364ms,total=0.210152ms,count=244]java.util.List:iterator()#164
+---[min=3.07E-4ms,max=0.199649ms,total=143.267893ms,count=351604]java.util.Iterator:hasNext()#164
+---[min=3.25E-4ms,max=24.863976ms,total=177.15363ms,count=351360]java.util.Iterator:next()#164
+---[min=3.93E-4ms,max=0.096771ms,total=176.843018ms,count=351360]xxxService.helios.entity.HeliosScore:getTimeFrom()#165
+---[min=4.07E-4ms,max=18.772715ms,total=205.632183ms,count=351360]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#165
+---[min=3.33E-4ms,max=0.045589ms,total=149.24486ms,count=351360]java.util.Date:compareTo()#165
+---[min=3.93E-4ms,max=0.032972ms,total=86.466793ms,count=175680]xxxService.helios.entity.HeliosScore:getTimeFrom()#168
+---[min=4.12E-4ms,max=0.061003ms,total=94.294061ms,count=175680]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#168
+---[min=3.37E-4ms,max=0.038792ms,total=74.505056ms,count=175680]java.util.Date:compareTo()#168
+---[min=3.97E-4ms,max=0.036548ms,total=87.693935ms,count=175680]xxxService.helios.entity.HeliosScore:getTimeFrom()#171
1+---[min=0.001952ms,max=0.068413ms,total=391.739063ms,count=175680]xxxService.utils.DateUtils$yyyyMMddHHmm:formatDate()#171
+---[min=4.07E-4ms,max=0.037904ms,total=108.107714ms,count=175680]java.util.Set:add()#171
+---[min=3.95E-4ms,max=0.031555ms,total=88.173857ms,count=175680]xxxService.helios.entity.HeliosScore:getScores()#172
+---[min=3.88E-4ms,max=0.033584ms,total=84.689466ms,count=175680]xxxService.helios.entity.HeliosScore:getScores()#176
+---[min=3.11E-4ms,max=0.038121ms,total=69.708752ms,count=175680]java.lang.Math:max()#176
+---[min=4.66E-4ms,max=0.03391ms,total=104.476576ms,count=175680]xxxService.model.helios.HeliosGetScoreResponse$Score:add()#176
+---[min=6.17E-4ms,max=0.01503ms,total=0.159826ms,count=122]xxxService.model.helios.HeliosGetScoreResponse:getValues()#179
+---[min=6.44E-4ms,max=0.03742ms,total=0.21068ms,count=122]java.util.List:add()#179
+---[0.108961ms]java.util.ArrayList:()#182
+---[0.017455ms]java.util.ArrayList:stream()#182
+---[0.011099ms]java.util.stream.Stream:sorted()#182
+---[0.013699ms]java.util.stream.Collectors:toList()#182
+---[0.38178ms]java.util.stream.Stream:collect()#182
`---[0.004627ms]xxxService.model.helios.HeliosGetScoreResponse:setDates()#182
分析
Arthas 显示总共花了 4 秒，但实际上在链路上看大概是 350~450ms 左右。其他多出来的时间是 Arthas 每一次执行统计的消耗，因为方法里的循环比较多。这也告诉我们，不要用 trace 去看循环很多的方法。会对性能有非常严重的影响。
可以看出整个函数有 3 个循环，第一层循环的数量为 appId 的数量约为 140，第二层是查出来的数据条数，一天的数据已经归并了所以这里应该是 1，第三层是时间区间的分钟数，一天的话就是 1440 个。
Trace 中可以看到消耗最多的是封装的一个 SimpleDateFormat.formatDate()。
4第一次优化
优化方向
遍历每个时间点的思路改变，把合并过的大对象拆分成一个个小对象直接遍历，改成先合并起来，通过时间点逻辑上遍历。这样会减少创建几十万个对象。
将时间点集合 Set 改为 Set，这样减少反复 formatDate() 的开销。
优化字符串转数字的过程，减少 Integer.parseInt方法调用，改为用 Map 提前创建出 0~100 的字符串数字字典。（后来经过 JMH 测试，还是 Integer.parseInt 最快）
代码
privateHeliosGetScoreResponsequeryScores(HeliosGetScoreRequestrequest){
HeliosGetScoreResponseresponse=newHeliosGetScoreResponse();
ListheliosScoresRecord=heliosService.queryScoresTimeBetween(request.getStartTime(),request.getEndTime(),request.getFilterByAppId());
if(CollectionUtils.isEmpty(heliosScoresRecord)){
returnresponse;
}
SetdateSet=newHashSet<>();
ListheliosScores=HeliosDataMergeJob.mergeData(heliosScoresRecord);
Map>groupByAppIdHeliosScores=heliosScores.stream().collect(Collectors.groupingBy(HeliosScore::getAppId));
for(Listscores:groupByAppIdHeliosScores.values()){
HeliosScoreheliosScore=scores.get(0);
HeliosGetScoreResponse.Scorescore=newHeliosGetScoreResponse.Score();
score.setNamespace(heliosScore.getNamespace());
score.setAppId(heliosScore.getAppId());
score.setScores(newArrayList<>());
response.getValues().add(score);
ListscoreIntList=HeliosHelper.splitScores(heliosScore);
//以requestTime为准
CalendarindexDate=DateUtils.roundDownMinute(request.getStartTime().getTime());
intindex=0;
//如果timeFrom< requestTime，则增加 timeFrom 到 requestTime
while(indexDate.getTime().compareTo(heliosScore.getTimeFrom())>0){
heliosScore.getTimeFrom().setTime(heliosScore.getTimeFrom().getTime()+60_000);
index++;
}
while(indexDate.getTime().compareTo(request.getEndTime())<= 0&&indexDate.getTime().compareTo(heliosScore.getTimeTo())<= 0&&index< scoreIntList.size()) {
Integer scoreInt = scoreIntList.get(index++);
score.getScores().add(scoreInt);
dateSet.add(indexDate.getTime());
indexDate.add(Calendar.MINUTE, 1);
}
}
response.setDates(newArrayList<>(dateSet).stream().sorted().map(DateUtils.yyyyMMddHHmm::formatDate).collect(Collectors.toList()));
returnresponse;
}
Arthas Trace
---ts=2021-08-1714:44:11;thread_name=http-nio-8080-exec-10;id=ab;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@16ea0f22
`---[6997.005629ms]xxxService.controller.HeliosController:queryScores()
+---[0.020032ms]xxxService.model.helios.HeliosGetScoreResponse:()#149
+---[0.007451ms]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#151
+---[min=0.001054ms,max=7.458198ms,total=213.19538ms,count=170754]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#57
+---[0.007267ms]xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId()#57
+---[15.255919ms]xxxService.service.HeliosService:queryScoresTimeBetween()#57
+---[0.020045ms]org.apache.commons.collections.CollectionUtils:isEmpty()#152
+---[0.015161ms]java.util.HashSet:()#156
+---[20.06713ms]xxxService.helios.jobs.HeliosDataMergeJob:mergeData()#158
+---[0.043042ms]java.util.List:stream()#160
+---[0.028232ms]java.util.stream.Collectors:groupingBy()#57
+---[min=0.087087ms,max=1.931641ms,total=2.018728ms,count=2]java.util.stream.Stream:collect()#57
+---[0.0151ms]java.util.Map:values()#162
+---[0.019611ms]java.util.Collection:iterator()#57
+---[min=7.55E-4ms,max=0.015165ms,total=0.201221ms,count=121]java.util.Iterator:hasNext()#57
+---[min=0.001178ms,max=0.02477ms,total=0.220931ms,count=120]java.util.Iterator:next()#57
+---[min=8.14E-4ms,max=0.01101ms,total=0.155044ms,count=120]java.util.List:get()#163
+---[min=0.001049ms,max=0.009425ms,total=0.231297ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:()#164
+---[min=0.001167ms,max=0.009721ms,total=0.194502ms,count=120]xxxService.helios.entity.HeliosScore:getNamespace()#165
+---[min=0.001222ms,max=0.020409ms,total=0.264791ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace()#57
+---[min=0.001097ms,max=0.006475ms,total=0.169987ms,count=120]xxxService.helios.entity.HeliosScore:getAppId()#166
+---[min=0.00121ms,max=0.007106ms,total=0.207877ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId()#57
+---[min=8.63E-4ms,max=0.008981ms,total=0.176195ms,count=120]java.util.ArrayList:()#167
+---[min=0.001225ms,max=0.021948ms,total=0.340375ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setScores()#57
+---[min=0.00112ms,max=0.008984ms,total=0.196212ms,count=120]xxxService.model.helios.HeliosGetScoreResponse:getValues()#168
+---[min=7.64E-4ms,max=0.027237ms,total=154.660479ms,count=170753]java.util.List:add()#57
+---[min=0.028779ms,max=0.237608ms,total=20.049731ms,count=120]xxxService.helios.HeliosHelper:splitScores()#170
+---[min=0.001178ms,max=0.008102ms,total=0.199087ms,count=120]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#173
+---[min=6.89E-4ms,max=0.048069ms,total=140.74298ms,count=170040]java.util.Date:getTime()#57
+---[min=0.004686ms,max=0.03805ms,total=0.775394ms,count=120]xxxService.utils.DateUtils:roundDownMinute()#57
+---[min=7.84E-4ms,max=7.562581ms,total=162.855553ms,count=170040]java.util.Calendar:getTime()#176
2+---[min=9.94E-4ms,max=0.029962ms,total=385.371864ms,count=339960]xxxService.helios.entity.HeliosScore:getTimeFrom()#57
1+---[min=7.76E-4ms,max=7.936578ms,total=483.361269ms,count=511428]java.util.Date:compareTo()#57
+---[min=9.95E-4ms,max=0.077109ms,total=192.749805ms,count=169920]xxxService.helios.entity.HeliosScore:getTimeFrom()#177
+---[min=6.94E-4ms,max=7.358942ms,total=151.184751ms,count=169920]java.util.Date:setTime()#57
+---[min=7.67E-4ms,max=0.029244ms,total=152.500401ms,count=170753]java.util.Calendar:getTime()#181
+---[min=7.65E-4ms,max=0.016336ms,total=151.879643ms,count=170635]java.util.Calendar:getTime()#182
+---[min=0.001011ms,max=0.028133ms,total=196.192946ms,count=170635]xxxService.helios.entity.HeliosScore:getTimeTo()#57
+---[min=6.93E-4ms,max=0.836104ms,total=141.443001ms,count=170635]java.util.List:size()#57
+---[min=7.63E-4ms,max=7.940119ms,total=162.285955ms,count=170633]java.util.List:get()#183
3+---[min=0.001068ms,max=0.973964ms,total=209.721ms,count=170633]xxxService.model.helios.HeliosGetScoreResponse$Score:getScores()#184
+---[min=7.71E-4ms,max=0.028856ms,total=154.918574ms,count=170633]java.util.Calendar:getTime()#185
+---[min=8.07E-4ms,max=8.030316ms,total=186.971072ms,count=170633]java.util.Set:add()#57
+---[min=7.82E-4ms,max=0.034732ms,total=156.2645ms,count=170633]java.util.Calendar:add()#186
+---[0.050615ms]java.util.ArrayList:()#190
+---[0.019114ms]java.util.ArrayList:stream()#57
+---[0.029096ms]java.util.stream.Stream:sorted()#57
+---[0.018823ms]java.util.stream.Stream:map()#57
+---[0.009092ms]java.util.stream.Collectors:toList()#57
`---[0.006768ms]xxxService.model.helios.HeliosGetScoreResponse:setDates()#57
分析
这一步实际上执行时间优化了 50ms 左右。
从 Trace 中看耗时时间最长的是 Date 的 compareTo，也就是代码中的 if (splitHeliosScore.getTimeFrom().compareTo(request.getStartTime()) < 0)
而比较意外的是从对象中 get 属性居然也是有开销的。
5第二次优化
优化方向
结合上一次 Arthas Trace 的结果，在以下几个方向进行优化：
- 将 Date 对象的换成 long 型时间戳进行比较
- 将 Date 对象反复 getTime、setTime，改为 long 型时间戳 += 60_000 实现，得到结果后只 setTime 一次。
-
每次填充数据都往
Set放入数据，改为通过标识判断只放入一次。dateSet - 存放分数的 ArrayList 在第一次循环之后，可以确认大小，之后循环创建 ArrayList 时直接填入固定的大小，减少内存创建。
代码
privateHeliosGetScoreResponsequeryScores(HeliosGetScoreRequestrequest){
HeliosGetScoreResponseresponse=newHeliosGetScoreResponse();
ListheliosScoresRecord=heliosService.queryScoresTimeBetween(request.getStartTime(),request.getEndTime(),request.getFilterByAppId());
if(CollectionUtils.isEmpty(heliosScoresRecord)){
returnresponse;
}
SetdateSet=newHashSet<>();
booleanisDateSetInitial=false;
intscoreSize=16;
ListheliosScores=HeliosDataMergeJob.mergeData(heliosScoresRecord);
Map>groupByAppIdHeliosScores=heliosScores.stream().collect(Collectors.groupingBy(HeliosScore::getAppId));
for(Listscores:groupByAppIdHeliosScores.values()){
HeliosScoreheliosScore=scores.get(0);
HeliosGetScoreResponse.Scorescore=newHeliosGetScoreResponse.Score();
score.setNamespace(heliosScore.getNamespace());
score.setAppId(heliosScore.getAppId());
score.setScores(newArrayList<>(scoreSize));
response.getValues().add(score);
ListscoreIntList=HeliosHelper.splitScores(heliosScore);
//以requestTime为准
longindexDateMills=request.getStartTime().getTime();
intindex=0;
//如果timeFrom< requestTime，则增加 timeFrom 到 requestTime
longheliosScoreTimeFromMills=heliosScore.getTimeFrom().getTime();
while(indexDateMills>heliosScoreTimeFromMills){
heliosScoreTimeFromMills+=60_000;
index++;
}
heliosScore.getTimeFrom().setTime(heliosScoreTimeFromMills);
longrequestEndTimeMills=request.getEndTime().getTime();
longheliosScoreTimeToMills=heliosScore.getTimeTo().getTime();
//循环条件为(当前时间<= 请求最大时间) && (当前时间 <= 数据最大时间) && (index < 数据条数)
while(indexDateMills<= requestEndTimeMills && indexDateMills <= heliosScoreTimeToMills && index < scoreIntList.size()) {
score.getScores().add(scoreIntList.get(index++));
if(!isDateSetInitial){
dateSet.add(newDate(indexDateMills));
}
indexDateMills+=60_000;
}
//性能优化，减少重复放入的次数
isDateSetInitial=true;
//性能优化，初始化足够的size减少扩容次数。x1.1为了万一数据数量不一致，留出一点buffer。
scoreSize=(int)(score.getScores().size()*1.1);
}
response.setDates(newArrayList<>(dateSet).stream().sorted().map(DateUtils.yyyyMMddHHmm::formatDate).collect(Collectors.toList()));
returnresponse;
}
Arthas Trace
---ts=2021-08-1715:20:41;thread_name=http-nio-8080-exec-7;id=aa;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@14be750c
`---[1411.395123ms]xxxService.controller.HeliosController:queryScores()
+---[0.016102ms]xxxService.model.helios.HeliosGetScoreResponse:()#149
+---[0.019084ms]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#151
+---[0.007879ms]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#57
+---[0.006808ms]xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId()#57
+---[27.494178ms]xxxService.service.HeliosService:queryScoresTimeBetween()#57
+---[0.02087ms]org.apache.commons.collections.CollectionUtils:isEmpty()#152
+---[0.007694ms]java.util.HashSet:()#156
+---[19.990512ms]xxxService.helios.jobs.HeliosDataMergeJob:mergeData()#160
+---[0.044161ms]java.util.List:stream()#162
+---[0.025737ms]java.util.stream.Collectors:groupingBy()#57
+---[min=0.079651ms,max=2.007048ms,total=2.086699ms,count=2]java.util.stream.Stream:collect()#57
+---[0.018405ms]java.util.Map:values()#164
+---[0.021408ms]java.util.Collection:iterator()#57
+---[min=7.4E-4ms,max=0.015625ms,total=0.177657ms,count=121]java.util.Iterator:hasNext()#57
+---[min=0.001193ms,max=0.026712ms,total=0.258491ms,count=120]java.util.Iterator:next()#57
+---[min=7.69E-4ms,max=0.011855ms,total=0.158671ms,count=120]java.util.List:get()#165
+---[min=0.001045ms,max=0.019788ms,total=0.232004ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:()#166
+---[min=0.001072ms,max=0.007958ms,total=0.193652ms,count=120]xxxService.helios.entity.HeliosScore:getNamespace()#167
+---[min=0.001164ms,max=0.007796ms,total=0.201584ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace()#57
+---[min=0.001048ms,max=0.007456ms,total=0.178323ms,count=120]xxxService.helios.entity.HeliosScore:getAppId()#168
+---[min=0.001137ms,max=0.010225ms,total=0.201887ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId()#57
+---[min=0.001627ms,max=0.010431ms,total=0.291395ms,count=120]java.util.ArrayList:()#169
+---[min=0.00116ms,max=0.0088ms,total=0.20171ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setScores()#57
+---[min=0.001076ms,max=0.010293ms,total=0.199407ms,count=120]xxxService.model.helios.HeliosGetScoreResponse:getValues()#170
+---[min=7.54E-4ms,max=0.086952ms,total=150.86682ms,count=170753]java.util.List:add()#57
+---[min=0.020428ms,max=0.269554ms,total=19.477128ms,count=120]xxxService.helios.HeliosHelper:splitScores()#172
+---[min=0.001092ms,max=0.005258ms,total=0.202045ms,count=120]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#175
+---[min=7.09E-4ms,max=0.021027ms,total=0.630747ms,count=480]java.util.Date:getTime()#57
+---[min=0.00106ms,max=0.015055ms,total=0.188439ms,count=120]xxxService.helios.entity.HeliosScore:getTimeFrom()#178
+---[min=0.001025ms,max=0.009712ms,total=0.171506ms,count=120]xxxService.helios.entity.HeliosScore:getTimeFrom()#183
+---[min=7.4E-4ms,max=0.092253ms,total=0.251068ms,count=120]java.util.Date:setTime()#57
+---[min=0.001086ms,max=0.006234ms,total=0.184256ms,count=120]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#185
+---[min=0.001036ms,max=0.012332ms,total=0.176491ms,count=120]xxxService.helios.entity.HeliosScore:getTimeTo()#186
3+---[min=6.73E-4ms,max=0.066785ms,total=135.009239ms,count=170635]java.util.List:size()#188
1+---[min=0.001085ms,max=0.089243ms,total=208.003309ms,count=170633]xxxService.model.helios.HeliosGetScoreResponse$Score:getScores()#189
2+---[min=7.31E-4ms,max=0.070823ms,total=145.488732ms,count=170633]java.util.List:get()#57
+---[min=0.001177ms,max=0.143546ms,total=2.319379ms,count=1440]java.util.Date:()#191
+---[min=0.001346ms,max=0.064411ms,total=2.839878ms,count=1440]java.util.Set:add()#57
+---[min=0.001096ms,max=0.009059ms,total=0.190336ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:getScores()#198
+---[min=6.92E-4ms,max=0.016223ms,total=0.141751ms,count=120]java.util.List:size()#57
+---[0.069753ms]java.util.ArrayList:()#201
+---[0.021066ms]java.util.ArrayList:stream()#57
+---[0.029498ms]java.util.stream.Stream:sorted()#57
+---[0.014089ms]java.util.stream.Stream:map()#57
+---[0.013053ms]java.util.stream.Collectors:toList()#57
`---[0.009818ms]xxxService.model.helios.HeliosGetScoreResponse:setDates()#57
分析
这一步将执行时间又优化了 80ms 左右。现在还剩是 160ms 了。
从 Trace 中看耗时时间最长的是三个方法：
-
getScores直接 get 了属性啥也没干，但是积少成多 -
list.size() -
list.get(index)
也就是说虽然这几个函数里也没干什么东西，但是函数调用、指针寻址本身也是有开销的。
6第三次优化
优化方向
- 减少 list 属性的调用
-
一次次
list.add方法改成 subList 一次性放入
也就是说循环中不做任何耗时操作，不做任何指针/引用。
代码
privateHeliosGetScoreResponsequeryScores(HeliosGetScoreRequestrequest){
HeliosGetScoreResponseresponse=newHeliosGetScoreResponse();
ListheliosScoresRecord=heliosService.queryScoresTimeBetween(request.getStartTime(),request.getEndTime(),request.getFilterByAppId());
if(CollectionUtils.isEmpty(heliosScoresRecord)){
returnresponse;
}
SetdateSet=newHashSet<>();
booleanisDateSetInitial=false;
intscoreSize=16;
ListheliosScores=HeliosDataMergeJob.mergeData(heliosScoresRecord);
Map>groupByAppIdHeliosScores=heliosScores.stream().collect(Collectors.groupingBy(HeliosScore::getAppId));
for(Listscores:groupByAppIdHeliosScores.values()){
HeliosScoreheliosScore=scores.get(0);
HeliosGetScoreResponse.Scorescore=newHeliosGetScoreResponse.Score();
score.setNamespace(heliosScore.getNamespace());
score.setAppId(heliosScore.getAppId());
score.setScores(newArrayList<>(scoreSize));
response.getValues().add(score);
ListscoreIntList=HeliosHelper.splitScores(heliosScore);
//以requestTime为准
longindexDateMills=request.getStartTime().getTime();
intindex=0;
//如果timeFrom< requestTime，则增加 timeFrom 到 requestTime
longheliosScoreTimeFromMills=heliosScore.getTimeFrom().getTime();
while(indexDateMills>heliosScoreTimeFromMills){
heliosScoreTimeFromMills+=60_000;
index++;
}
heliosScore.getTimeFrom().setTime(heliosScoreTimeFromMills);
longrequestEndTimeMills=request.getEndTime().getTime();
longheliosScoreTimeToMills=heliosScore.getTimeTo().getTime();
//循环条件为(当前时间<= 请求最大时间) && (当前时间 <= 数据最大时间) && (index < 数据条数)
intscoreIntListSize=scoreIntList.size();
intindexStart=index;
while(indexDateMills<= requestEndTimeMills && indexDateMills <= heliosScoreTimeToMills && index++ < scoreIntListSize) {
if(!isDateSetInitial){
dateSet.add(newDate(indexDateMills));
}
indexDateMills+=60_000;
}
score.getScores().addAll(scoreIntList.subList(indexStart,index-1));
//性能优化，减少重复放入的次数
isDateSetInitial=true;
//性能优化，初始化足够的size减少扩容次数。x1.1为了万一数据数量不一致，留出一点buffer。
scoreSize=(int)(score.getScores().size()*1.1);
}
response.setDates(newArrayList<>(dateSet).stream().sorted().map(DateUtils.yyyyMMddHHmm::formatDate).collect(Collectors.toList()));
returnresponse;
}
Arthas Trace
---ts=2021-08-1715:33:40;thread_name=http-nio-8080-exec-11;id=f1;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@d1c5cf2
`---[138.624811ms]xxxService.controller.HeliosController:queryScores()
+---[0.021852ms]xxxService.model.helios.HeliosGetScoreResponse:()#149
+---[0.00746ms]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#151
+---[0.005838ms]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#57
+---[0.006341ms]xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId()#57
2+---[15.227453ms]xxxService.service.HeliosService:queryScoresTimeBetween()#57
+---[0.02168ms]org.apache.commons.collections.CollectionUtils:isEmpty()#152
+---[0.008923ms]java.util.HashSet:()#156
1+---[22.703926ms]xxxService.helios.jobs.HeliosDataMergeJob:mergeData()#160
+---[0.047118ms]java.util.List:stream()#162
+---[0.043183ms]java.util.stream.Collectors:groupingBy()#57
+---[min=0.095654ms,max=2.183288ms,total=2.278942ms,count=2]java.util.stream.Stream:collect()#57
+---[0.022906ms]java.util.Map:values()#164
+---[0.025777ms]java.util.Collection:iterator()#57
+---[min=9.28E-4ms,max=0.017187ms,total=0.261862ms,count=121]java.util.Iterator:hasNext()#57
+---[min=9.88E-4ms,max=0.018901ms,total=0.280889ms,count=120]java.util.Iterator:next()#57
+---[min=9.65E-4ms,max=0.014741ms,total=0.262695ms,count=120]java.util.List:get()#165
+---[min=0.001215ms,max=0.013928ms,total=0.347762ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:()#166
+---[min=0.001253ms,max=0.010855ms,total=0.328842ms,count=120]xxxService.helios.entity.HeliosScore:getNamespace()#167
+---[min=0.001316ms,max=0.014714ms,total=0.372553ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace()#57
+---[min=0.001211ms,max=0.010511ms,total=0.322723ms,count=120]xxxService.helios.entity.HeliosScore:getAppId()#168
+---[min=0.00132ms,max=0.010201ms,total=0.334627ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId()#57
+---[min=0.00116ms,max=0.014504ms,total=0.386879ms,count=120]java.util.ArrayList:()#169
+---[min=0.00131ms,max=0.014072ms,total=0.344922ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setScores()#57
+---[min=0.001261ms,max=0.017312ms,total=0.356444ms,count=120]xxxService.model.helios.HeliosGetScoreResponse:getValues()#170
+---[min=9.73E-4ms,max=0.016531ms,total=0.275794ms,count=120]java.util.List:add()#57
3+---[min=0.023208ms,max=19.808819ms,total=47.196601ms,count=120]xxxService.helios.HeliosHelper:splitScores()#172
+---[min=0.001289ms,max=0.009578ms,total=0.36878ms,count=120]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#175
+---[min=8.85E-4ms,max=0.016405ms,total=0.994157ms,count=480]java.util.Date:getTime()#57
+---[min=0.001238ms,max=0.016801ms,total=0.34399ms,count=120]xxxService.helios.entity.HeliosScore:getTimeFrom()#178
+---[min=0.001217ms,max=0.008931ms,total=0.316197ms,count=120]xxxService.helios.entity.HeliosScore:getTimeFrom()#183
+---[min=9.14E-4ms,max=0.015929ms,total=0.277078ms,count=120]java.util.Date:setTime()#57
+---[min=0.001238ms,max=0.01061ms,total=0.3375ms,count=120]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#185
+---[min=0.001225ms,max=0.018059ms,total=0.315198ms,count=120]xxxService.helios.entity.HeliosScore:getTimeTo()#186
+---[min=8.79E-4ms,max=0.022669ms,total=0.272356ms,count=120]java.util.List:size()#189
+---[min=0.002001ms,max=0.056977ms,total=4.32853ms,count=1440]java.util.Date:()#193
+---[min=0.002174ms,max=0.040594ms,total=4.594415ms,count=1440]java.util.Set:add()#57
+---[min=0.001302ms,max=0.012925ms,total=0.353165ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:getScores()#197
+---[min=0.001004ms,max=0.033424ms,total=0.338294ms,count=120]java.util.List:subList()#57
+---[min=0.004871ms,max=0.051046ms,total=2.945263ms,count=120]java.util.List:addAll()#57
+---[min=0.001291ms,max=0.009831ms,total=0.314292ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:getScores()#201
+---[min=8.84E-4ms,max=0.018168ms,total=0.249321ms,count=120]java.util.List:size()#57
+---[0.054305ms]java.util.ArrayList:()#204
+---[0.024481ms]java.util.ArrayList:stream()#57
+---[0.028717ms]java.util.stream.Stream:sorted()#57
+---[0.013725ms]java.util.stream.Stream:map()#57
+---[0.0128ms]java.util.stream.Collectors:toList()#57
`---[0.007166ms]xxxService.model.helios.HeliosGetScoreResponse:setDates()#57
分析
这一步又优化了 100ms 左右，现在还剩 60ms。
现在从 trace 上看耗时操作只有三个了：
- 查数据库
- 合并数据
-
拆分得分字符串 "
100,100,100" 为 int 数组[100,100,100]
7第四次优化
优化方向
查数据库发现由于 SQL 判断不准确，每次会多查出来一条数据，在后边循环的时候会多循环一倍
合并数据时发现可以针对单条数据的情况直接过滤，减少开销。
代码
- 改了 SQL 并验证，减少查询出来的数据量
- 单条数据时不再处理合并逻辑
Arthas Trace
---ts=2021-08-1716:03:24;thread_name=http-nio-8080-exec-13;id=f1;is_daemon=true;priority=5;TCCL=org.springframework.boot.web.embedded.tomcat.TomcatEmbeddedWebappClassLoader@69e2fe3b
`---[38.171379ms]xxxService.controller.HeliosController:queryScores()
+---[0.009463ms]xxxService.model.helios.HeliosGetScoreResponse:()#149
+---[0.00348ms]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#151
+---[0.003233ms]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#57
+---[0.003395ms]xxxService.model.helios.HeliosGetScoreRequest:getFilterByAppId()#57
1+---[10.157226ms]xxxService.service.HeliosService:queryScoresTimeBetween()#57
+---[0.009989ms]org.apache.commons.collections.CollectionUtils:isEmpty()#152
+---[0.003394ms]java.util.HashSet:()#156
+---[0.083535ms]xxxService.helios.jobs.HeliosDataMergeJob:mergeData()#160
+---[0.017819ms]java.util.List:stream()#162
+---[0.011787ms]java.util.stream.Collectors:groupingBy()#57
+---[min=0.047561ms,max=2.02786ms,total=2.075421ms,count=2]java.util.stream.Stream:collect()#57
+---[0.015525ms]java.util.Map:values()#164
+---[0.021965ms]java.util.Collection:iterator()#57
+---[min=7.25E-4ms,max=0.009733ms,total=0.115783ms,count=121]java.util.Iterator:hasNext()#57
+---[min=8.43E-4ms,max=0.011422ms,total=0.142771ms,count=120]java.util.Iterator:next()#57
+---[min=7.81E-4ms,max=0.010883ms,total=0.128809ms,count=120]java.util.List:get()#165
+---[min=0.001023ms,max=0.004301ms,total=0.150165ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:()#166
+---[min=0.001066ms,max=0.004648ms,total=0.154698ms,count=120]xxxService.helios.entity.HeliosScore:getNamespace()#167
+---[min=0.001137ms,max=0.005607ms,total=0.170279ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setNamespace()#57
+---[min=0.001023ms,max=0.004292ms,total=0.151767ms,count=120]xxxService.helios.entity.HeliosScore:getAppId()#168
+---[min=0.001105ms,max=0.004701ms,total=0.164955ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setAppId()#57
+---[min=0.001359ms,max=0.007931ms,total=0.233665ms,count=120]java.util.ArrayList:()#169
+---[min=0.001117ms,max=0.00785ms,total=0.168539ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:setScores()#57
+---[min=0.001073ms,max=0.004488ms,total=0.156654ms,count=120]xxxService.model.helios.HeliosGetScoreResponse:getValues()#170
+---[min=7.98E-4ms,max=0.00977ms,total=0.125818ms,count=120]java.util.List:add()#57
+---[min=0.022304ms,max=0.12093ms,total=8.88628ms,count=120]xxxService.helios.HeliosHelper:splitScores()#172
+---[min=0.001092ms,max=0.004967ms,total=0.161288ms,count=120]xxxService.model.helios.HeliosGetScoreRequest:getStartTime()#175
+---[min=7.02E-4ms,max=0.012136ms,total=0.467786ms,count=480]java.util.Date:getTime()#57
+---[min=0.001022ms,max=0.004944ms,total=0.151353ms,count=120]xxxService.helios.entity.HeliosScore:getTimeFrom()#178
+---[min=0.001018ms,max=0.004731ms,total=0.148025ms,count=120]xxxService.helios.entity.HeliosScore:getTimeFrom()#183
+---[min=7.3E-4ms,max=0.009359ms,total=0.120588ms,count=120]java.util.Date:setTime()#57
+---[min=0.00107ms,max=0.008948ms,total=0.162848ms,count=120]xxxService.model.helios.HeliosGetScoreRequest:getEndTime()#185
+---[min=0.001034ms,max=0.014003ms,total=0.158614ms,count=120]xxxService.helios.entity.HeliosScore:getTimeTo()#186
+---[min=6.99E-4ms,max=0.009995ms,total=0.11179ms,count=120]java.util.List:size()#189
+---[min=6.95E-4ms,max=0.005468ms,total=1.116308ms,count=1440]java.util.Date:()#193
+---[min=7.79E-4ms,max=0.029909ms,total=1.407528ms,count=1440]java.util.Set:add()#57
+---[min=0.001097ms,max=0.008616ms,total=0.160597ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:getScores()#197
+---[min=8.23E-4ms,max=0.0294ms,total=0.153353ms,count=120]java.util.List:subList()#57
+---[min=0.005771ms,max=0.04465ms,total=1.992151ms,count=120]java.util.List:addAll()#57
+---[min=0.001098ms,max=0.007013ms,total=0.169555ms,count=120]xxxService.model.helios.HeliosGetScoreResponse$Score:getScores()#201
+---[min=7.04E-4ms,max=0.01315ms,total=0.120998ms,count=120]java.util.List:size()#57
+---[0.197732ms]java.util.ArrayList:()#204
+---[0.018589ms]java.util.ArrayList:stream()#57
+---[0.025192ms]java.util.stream.Stream:sorted()#57
+---[0.012544ms]java.util.stream.Stream:map()#57
+---[0.012188ms]java.util.stream.Collectors:toList()#57
`---[0.0067ms]xxxService.model.helios.HeliosGetScoreResponse:setDates()#57
分析
可以看到现在最大耗时的地方终于是数据库查询了。现在查询一整天的数据，也只需要 25~40ms 左右。
8结果
链路
链路上看程序代码还是要处理个十几 ms，主要是字符串转 int[] 时的开销，这一步可以再想办法继续优化。 结论
从这次优化我们可以得到一些结论：
1、尽量少创建对象
2、SimpleDateFormat的开销很大
3、Date.compare 的开销不低
4、哪怕最简单的操作如 list.size() list.add次数多了开销也很可观
5、对于性能分析和优化一定要有合适工具，才能得出有用的结论并针对性优化。一开始我以为减少对象创建就万事大吉，但实际上性能消耗的大头并不在这里。还是得借助 Arthas 的 Trace 才能真正针对性地优化
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原文标题：接口性能优化十倍，来了解一下 Arthas 的强大！
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